Let’s define some vectors which can be used for demonstrations:
manyNumbers <- sample( 1:1000, 20 )
manyNumbers
[1] 340 553 442 672 765 272 968 606 864 176 4 782 60 999 303 625 980 949 225 575
manyNumbersWithNA <- sample( c( NA, NA, NA, manyNumbers ) )
manyNumbersWithNA
[1] 999 176 575 606 980 949 765 340 672 303 272 225 782 864 442 60 4 625 NA NA 968 553 NA
duplicatedNumbers <- sample( 1:5, 10, replace = TRUE )
duplicatedNumbers
[1] 1 4 4 2 5 3 1 1 5 4
letters
[1] "a" "b" "c" "d" "e" "f" "g" "h" "i" "j" "k" "l" "m" "n" "o" "p" "q" "r" "s" "t" "u" "v" "w" "x" "y"
[26] "z"
LETTERS
[1] "A" "B" "C" "D" "E" "F" "G" "H" "I" "J" "K" "L" "M" "N" "O" "P" "Q" "R" "S" "T" "U" "V" "W" "X" "Y"
[26] "Z"
mixedLetters <- c( sample( letters, 5 ), sample( LETTERS, 5 ) )
mixedLetters
[1] "o" "q" "j" "t" "y" "A" "L" "B" "R" "Z"
manyNumbersWithNA instead of manyNumbers.all( manyNumbers <= 1000 )
[1] TRUE
all( manyNumbers <= 500 )
[1] FALSE
any( manyNumbers > 1000 )
[1] FALSE
any( manyNumbers > 500 )
[1] TRUE
all( !is.na( manyNumbers ) )
[1] TRUE
any( is.na( manyNumbers ) )
[1] FALSE
Input: logical vector Output: vector of numbers (positions)
which( manyNumbers > 900 )
[1] 7 14 17 18
which( manyNumbersWithNA > 900 )
[1] 1 5 6 21
which( is.na( manyNumbersWithNA ) )
[1] 19 20 23
manyNumbers[ manyNumbers > 900 ] # indexing by logical vector
[1] 968 999 980 949
manyNumbers[ which( manyNumbers > 900 ) ] # indexing by positions
[1] 968 999 980 949
somePositions <- which( manyNumbers > 900 )
manyNumbers[ somePositions ]
[1] 968 999 980 949
"A" %in% LETTERS
[1] TRUE
c( "X", "Y", "Z" ) %in% LETTERS
[1] TRUE TRUE TRUE
all( c( "X", "Y", "Z" ) %in% LETTERS )
[1] TRUE
all( mixedLetters %in% LETTERS )
[1] FALSE
any( mixedLetters %in% LETTERS )
[1] TRUE
mixedLetters[ mixedLetters %in% LETTERS ]
[1] "A" "L" "B" "R" "Z"
mixedLetters[ !( mixedLetters %in% LETTERS ) ]
[1] "o" "q" "j" "t" "y"
manyNumbers %in% 300:600
[1] TRUE TRUE TRUE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE TRUE FALSE FALSE
[18] FALSE FALSE TRUE
which( manyNumbers %in% 300:600 )
[1] 1 2 3 15 20
sum( manyNumbers %in% 300:600 )
[1] 5
NAsif_else( manyNumbersWithNA >= 500, "large", "small" )
[1] "large" "small" "large" "large" "large" "large" "large" "small" "large" "small" "small" "small"
[13] "large" "large" "small" "small" "small" "large" NA NA "large" "large" NA
if_else( manyNumbersWithNA >= 500, "large", "small", "UNKNOWN" )
[1] "large" "small" "large" "large" "large" "large" "large" "small" "large" "small"
[11] "small" "small" "large" "large" "small" "small" "small" "large" "UNKNOWN" "UNKNOWN"
[21] "large" "large" "UNKNOWN"
# here integer 0L is needed instead of real 0.0
# manyNumbersWithNA contains integer numbers and the method complains
if_else( manyNumbersWithNA >= 500, manyNumbersWithNA, 0L )
[1] 999 0 575 606 980 949 765 0 672 0 0 0 782 864 0 0 0 625 NA NA 968 553 NA
unique( duplicatedNumbers )
[1] 1 4 2 5 3
unique( c( NA, duplicatedNumbers, NA ) )
[1] NA 1 4 2 5 3
duplicated( duplicatedNumbers )
[1] FALSE FALSE TRUE FALSE FALSE FALSE TRUE TRUE TRUE TRUE
which.max( manyNumbersWithNA )
[1] 1
manyNumbersWithNA[ which.max( manyNumbersWithNA ) ]
[1] 999
which.min( manyNumbersWithNA )
[1] 17
manyNumbersWithNA[ which.min( manyNumbersWithNA ) ]
[1] 4
range( manyNumbersWithNA, na.rm = TRUE )
[1] 4 999
manyNumbersWithNA
[1] 999 176 575 606 980 949 765 340 672 303 272 225 782 864 442 60 4 625 NA NA 968 553 NA
sort( manyNumbersWithNA )
[1] 4 60 176 225 272 303 340 442 553 575 606 625 672 765 782 864 949 968 980 999
sort( manyNumbersWithNA, na.last = TRUE )
[1] 4 60 176 225 272 303 340 442 553 575 606 625 672 765 782 864 949 968 980 999 NA NA NA
sort( manyNumbersWithNA, na.last = TRUE, decreasing = TRUE )
[1] 999 980 968 949 864 782 765 672 625 606 575 553 442 340 303 272 225 176 60 4 NA NA NA
manyNumbersWithNA[1:5]
[1] 999 176 575 606 980
order( manyNumbersWithNA[1:5] )
[1] 2 3 4 5 1
rank( manyNumbersWithNA[1:5] )
[1] 5 1 2 3 4
sort( mixedLetters )
[1] "A" "B" "j" "L" "o" "q" "R" "t" "y" "Z"
manyDuplicates <- sample( 10:15, 10, replace = TRUE )
rank( manyDuplicates )
[1] 3.5 1.5 1.5 8.5 3.5 10.0 6.0 8.5 6.0 6.0
rank( manyDuplicates, ties.method = "min" )
[1] 3 1 1 8 3 10 5 8 5 5
rank( manyDuplicates, ties.method = "random" )
[1] 3 1 2 8 4 10 7 9 5 6
v <- c( -1, -0.5, 0, 0.5, 1, rnorm( 10 ) )
v
[1] -1.0000000 -0.5000000 0.0000000 0.5000000 1.0000000 0.5955782 0.7945390 -2.5213091 0.4879697
[10] 0.5194129 1.9074749 0.2373150 -0.7620926 0.9571338 -1.8722351
round( v, 0 )
[1] -1 0 0 0 1 1 1 -3 0 1 2 0 -1 1 -2
round( v, 1 )
[1] -1.0 -0.5 0.0 0.5 1.0 0.6 0.8 -2.5 0.5 0.5 1.9 0.2 -0.8 1.0 -1.9
round( v, 2 )
[1] -1.00 -0.50 0.00 0.50 1.00 0.60 0.79 -2.52 0.49 0.52 1.91 0.24 -0.76 0.96 -1.87
floor( v )
[1] -1 -1 0 0 1 0 0 -3 0 0 1 0 -1 0 -2
ceiling( v )
[1] -1 0 0 1 1 1 1 -2 1 1 2 1 0 1 -1
heights <- c( Amy = 166, Eve = 170, Bob = 177 )
heights
Amy Eve Bob
166 170 177
names( heights )
[1] "Amy" "Eve" "Bob"
names( heights ) <- c( "AMY", "EVE", "BOB" )
heights
AMY EVE BOB
166 170 177
heights[[ "EVE" ]]
[1] 170
expand_grid( x = c( 1:3, NA ), y = c( "a", "b" ) )
# A tibble: 8 × 2
x y
<int> <chr>
1 1 a
2 1 b
3 2 a
4 2 b
5 3 a
6 3 b
7 NA a
8 NA b
combn( c( "a", "b", "c", "d", "e" ), m = 2, simplify = TRUE )
[,1] [,2] [,3] [,4] [,5] [,6] [,7] [,8] [,9] [,10]
[1,] "a" "a" "a" "a" "b" "b" "b" "c" "c" "d"
[2,] "b" "c" "d" "e" "c" "d" "e" "d" "e" "e"
combn( c( "a", "b", "c", "d", "e" ), m = 3, simplify = TRUE )
[,1] [,2] [,3] [,4] [,5] [,6] [,7] [,8] [,9] [,10]
[1,] "a" "a" "a" "a" "a" "a" "b" "b" "b" "c"
[2,] "b" "b" "b" "c" "c" "d" "c" "c" "d" "d"
[3,] "c" "d" "e" "d" "e" "e" "d" "e" "e" "e"
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